Design and Development of an Automated Kiosk for COVID-19 Detection and Mitigation Using Machine Learning Algorithms

The Corona Virus Disease (COVID-19) is a contagious illness that has spread globally since December 2019. Coughing, sneezing, and even encountering objects used by an infected individual, is the possibility of Corona virus spreading. It is the utmost priority in today's time to control and mitigate this virus's spread. This is achieved by detecting some of the symptoms using non-clinical methods (as clinical methods are time-consuming), which detect the possibility of the presence of the virus in the human body. A solar-powered kiosk with a face-mask detector, a contactless temperature sensor, an oxygen saturation sensor, an automatic hand sanitizer dispenser, and an entry flip gate is designed and built to monitor and manage the spread of covid-19 illness. The kiosk system with a camera placed detects the facial mask of the person taking an entry using Machine Learning Algorithms (MLA). The system denies access to those without the mask and warns those whose masks are below the nose and denies entry through the Kiosk. Also, a contactless temperature sensor and SpO2 sensor in the Kiosk detect the threshold temperature and oxygen saturation level of the human for access entry. The automated contactless sanitizer is dispensed once the predefined parameters are met. When these tasks are completed, a flip gate will automatically open, allowing people to exit the Kiosk. The Kiosk is driven by a 10-watt solar PV (Photovoltaic) and from an electric outlet. The Raspberry Pi is the system's central processing unit, regulating several actuators. The Kiosk is portable and can be deployed in various locations, including malls, offices, and educational institutions.